The present disclosure relates to cloud computing, and more specifically, to automatic, analysis-based scheduling of jobs to appropriate cloud resources.
In current cloud computing environments, users must know how to select an image and system type to create an instance in the cloud to run their workload (or applications). This requires the user to have knowledge of the cloud topology and associated resources. As cloud computing moves to larger hybrid cloud environments, these problems will only be exacerbated. In addition, heterogeneous clouds that combine different types of hardware, software, and add-ons will further complicate user attempts to deploy their applications. Existing schedulers assume a homogeneous hardware environment with an appropriately pre-compiled binary file for the application.